DappDominator

The effectiveness of current AI models, to put it simply, depends on how strong people's questioning abilities are.
Many people complain that AI doesn't work well, but the root cause isn't the model itself—it's that the questions, context, and boundary conditions haven't been clearly defined. Vague descriptions lead AI to give mediocre answers. When questions are precise, the model can truly demonstrate its power.
Rest assured, it won't be replaced in the short term. Most users on Twitter haven't even thought through what to ask, let alone explain their questions clearly.
This logic also appli

4 new Ethscription ESIPs just dropped. These improvement proposals are pushing forward the development of Ethereum-based inscription standards and could open up fresh possibilities for on-chain data structures.

Ethereum's Tech Choice: Why RISC-V Won Over eWASM
At Pragma Taipei this April, Vitalik Buterin sat down to discuss one of Ethereum's most significant technical pivot points. The question on everyone's mind: why did the network move away from eWASM to RISC-V?
The story starts with ambition. eWASM was supposed to be the solution—a fresh replacement for the EVM's known limitations. Clean code, better performance, a real upgrade path. But execution is where theory meets reality.
Timing became the killer. While Ethereum pushed toward The Merge, eWASM development hit roadblocks. The delays stacked u

Which stocks are positioned to lead in 2026? Major institutional investors are betting big on AI-driven tech.
Nvidia continues to dominate the conversation. The chip giant's revenue trajectory remains impressive, and institutional money isn't slowing down. Why? Long-term AI adoption shows no signs of cooling—data centers, enterprise deployment, and infrastructure buildout will keep demand elevated through the decade.
Streaming giant Spotify is also catching attention for its AI capabilities. The platform's ability to leverage machine learning for user engagement and personalization presents re

Multi-Chain Support with COTI: The Next Evolution
COTI is building out comprehensive support for DApps regardless of where they're originally deployed. The network can seamlessly integrate with your existing infrastructure while ensuring that transactions and interactions are reflected not just on COTI's chain, but also on the origin chain simultaneously.
This multi-chain approach opens up new possibilities for developers. As $COTI token integration expands across different blockchain networks, we're seeing growing conversations around standardized interoperability solutions. The vision here i

Zero coding experience? No problem. I managed to spin up a fully interactive website using nothing but AI conversations. Seriously, just went back and forth with the model, describing what I wanted, and boom—functional web application. The AI basically handles all the technical heavy lifting while you focus on the logic and design.
It's wild how much this changes the game. Used to be you'd need months of learning to get anything off the ground. Now? Anyone with an idea can build something real in hours. The barrier to entry for Web3 creators, indie devs, and builders just got obliterated.

If you think about it, proper L2 solutions should function like certain meme-focused platforms do on L1—efficient, purpose-built, and actually solving real problems. That's the key difference.
Here's what makes this interesting: not every token needs to follow the same tokenomics playbook. Different projects, different mechanics. That flexibility? It's honestly what keeps the ecosystem healthy and innovative. Cookie-cutter approaches rarely create genuine utility.

The myth that technology just happens on its own? Total misconception. Breakthroughs in blockchain, AI, and any frontier tech don't materialize out of thin air—they're the result of relentless effort from thousands of developers, researchers, and engineers grinding it out. You want better protocols? Someone's gotta build them. Faster consensus mechanisms? Teams need to iterate, fail, and iterate again. The innovation we see in crypto today isn't magic; it's the product of countless late nights and unwavering commitment. The gap between what's possible and what actually exists is measured in sh

Picture this: a massive natural disaster strikes, cell towers collapse across an entire region, communication infrastructure lies in ruins. Yet your phone still maintains connection. This isn't science fiction—it's the emerging reality of resilient communication networks that don't depend on centralized infrastructure. The technology is advancing fast, and it could fundamentally reshape how information flows during crises and beyond.

Two practical ways to fine-tune your take-profit and stop-loss settings:
**Via the Chart Interface** — Simply drag the TP/SL lines directly on your chart to set or adjust your target levels in real-time. It's intuitive and gives you immediate visual feedback.
**Through Open Orders Tab** — Prefer a more detailed approach? Hit the [Edit] button to modify your TP/SL parameters with precision.
Both methods are available across web and mobile platforms. Just ensure you're running the latest app version to unlock this functionality. This feature streamlines position management and helps you execute

Swiss researchers just pulled off something wild—they're repurposing dead lobster shells to build biomechanical robots. The approach, called necrobotics, takes advantage of the lobster exoskeleton and creates manipulator arms that actually outperform conventional fully mechanical designs. It's the kind of out-of-the-box thinking that challenges how we think about material science and biological engineering. The exoskeleton provides structural integrity and unique articulation properties that synthetic materials struggle to replicate. Pretty interesting intersection of biology and robotics—when

AI agents need transparency—how do you know they're doing what they claim? On-chain verification is the answer.
Warden Protocol is pioneering an AI-native blockchain where agents publish their actions directly, and applications can validate those results using spex (statistical proof of execution). This bridges the trust gap between AI decision-making and blockchain verification.
The mainnet is currently running in limited access mode, gradually rolling out to early participants. It's a compelling approach to making AI behavior auditable and verifiable at the protocol level.

Turns out building this in plain vanilla JavaScript instead of reaching for React can actually work pretty well. Who knew?

If you're still out of the loop, MagicBlock is now rolling out Private Ephemeral Rollups powered by Intel TEE technology. Here's what that actually means: you're looking at sub-50ms execution times paired with compliance and verifiability built in. The use cases? Shielded trading that doesn't compromise speed, private AI inference without exposing your inputs, confidential gaming environments—all settling directly on-chain. No bridge hops, no liquidity fragmentation, no cross-chain middlemen taking their cut. It's a clean architecture for anyone tired of choosing between privacy and performanc

Picture this: a project launches groundbreaking tech, everyone hypes it as the next big thing. Unbeatable, they say. Then another protocol drops superior infrastructure—boom, the previous leader gets displaced. But wait, a third competitor emerges with even more advanced solutions and completely flips the game again. This cycle doesn't stop. The blockchain ecosystem thrives on continuous technological one-upmanship. Each iteration kills the last, every upgrade triggers the next wave of competition. That's the nature of Web3 development: innovation breeds disruption, and disruption breeds the n

Satellite internet continues its rapid expansion trajectory. The service reached 9 million users, adding 1 million subscriptions within just seven weeks—a significant acceleration in growth velocity.
The momentum is undeniable: daily user additions now exceed 20,000. The acceleration is particularly striking when comparing growth intervals. The jump from 7 million to 8 million took 69 days, but reaching 9 million from that point required only 48 days. This compression of timeline reflects growing demand and improving network reliability.
Context matters here. By late 2024, the platform operate

AI model training faces a real problem: errors can silently compound through feedback loops, creating blind spots that nobody catches until it's too late. Human oversight at every checkpoint changes the game entirely. When people stay involved throughout the training process—not just at the edges—it fundamentally shifts how the model learns. The results speak for themselves: higher accuracy, fewer hidden biases, and outputs that actually match what happens in the real world. This layered human-in-the-loop approach isn't just better technically; it's how you build AI systems people can actually

As AI surveillance systems expand globally, privacy-preserving technologies like zero-knowledge proofs are becoming critical. The clash between centralized monitoring and cryptographic privacy solutions will shape the future of Web3. zkproofs offer users a way to verify transactions and data without exposing sensitive information—positioning them as essential tools in the fight for digital autonomy.

The solution to the fragmentation problem in the L2 ecosystem lies in unified liquidity. Put simply, it involves using technical means to connect the liquidity scattered across various L2s, transforming the entire Ethereum system into a seamless network from the user's perspective.
How exactly to do this? First, achieve seamless cross-L2 asset transfer, allowing users to move assets directly between chains without repeatedly locking or unlocking liquidity. Second, build an abstraction layer for chains—hiding all the underlying details at the application layer so that users are unaware of which

BAL token has gone live on the Binance Smart Chain through the BEP-592 standard, bringing meaningful improvements to EVM execution efficiency.
The upgrade allows validator nodes to pre-fetch blockchain state data before processing transactions, eliminating the delays caused by mid-execution state discovery. This architectural improvement translates into tangible benefits across the network:
• Reduced computational load on validators (lower CPU overhead)
• Enhanced transaction throughput measured in MGas per second
• More stable and responsive transaction settlement
By optimizing how state info